**What Is Heap in Data Structure and Its Types?**

A heap is a specialized tree-based data structure that satisfies the heap property. The heap property states that for a given node, the value of the node is either greater than or equal to (in a max heap) or less than or equal to (in a min heap) the values of its children.

In other words, in a max heap, the maximum value is always at the root node, whereas in a min heap, the minimum value is at the root node.

## Types of Heaps

There are two main types of heaps: __max heaps__ and __min heaps__. Let’s explore each type in more detail.

### Max Heap

In a max heap, every parent node has a value greater than or equal to its children. This means that the maximum element will always be at the root of the tree.

Max heaps are commonly used in applications where we need quick access to the maximum element, such as priority queues and sorting algorithms like heapsort.

### Min Heap

In contrast to a max heap, every parent node in a min heap has a value less than or equal to its children. Consequently, the minimum element is always at the root of the tree.

Min heaps find applications in scenarios where we require quick access to the minimum element, such as Dijkstra’s algorithm for finding shortest paths.

## Implementation of Heap Data Structure

Heaps can be implemented as arrays or trees. When using an array representation, we can efficiently store and manipulate heaps due to their complete binary tree nature.

In this implementation, each element in the array corresponds to a node in the heap. The index of a node’s children or parent can be calculated using simple arithmetic operations.

To maintain the heap property, we need to perform heapify operations after each insertion or deletion. Heapify ensures that the heap property is satisfied by performing swaps between nodes until the property holds for all elements in the heap.

## Summary

In summary, a heap is a tree-based data structure that satisfies the heap property. This property guarantees that either the maximum or minimum value resides at the root node, depending on whether it is a max heap or min heap.

Heaps find applications in various algorithms and data structures where quick access to extreme values is required.